Global Poverty Trends: A Comprehensive Dataset for Research and Development

INFO 526 - Project Final

Project description
Author
Affiliation

InsightArchitect - Ayesha, Shreemithra, Anusha, Eeshaan, Kaarthik, Amaan

School of Information, University of Arizona

Abstract

This project by Insight Architect harnesses a comprehensive data-set on global poverty trends from Our World in Data to provide actionable insights into the dynamics of poverty across different regions and timelines. Utilizing advanced data visualization tools the shiny app in R, the project aims to enhance the understanding of poverty patterns and the effectiveness of various interventions.he dataset, encompassing 4,877 rows and 108 columns, is rich in metrics such as the headcount ratio at the international poverty line, Gini coefficients, and other inequality indices, which are crucial for analyzing poverty trends and wealth distribution among different income groups.

the project will address pivotal questions regarding the reduction of extreme poverty, the distribution of wealth, and the impact of welfare regimes and economic growth on income inequality. By focusing on these areas, the research intends to uncover the nuances of poverty alleviation efforts and economic policies across various global regions over the past three decades.

Introduction

Justification of approach

Stacked bar charts are effective for showing the total amount as well as the composition of that total. By presenting data on people living in and out of extreme poverty as parts of a whole for each year, this visualization clearly demonstrates how total populations and their poverty statuses have evolved over nearly two centuries

This visualization strategy leverages the strengths of stacked bar charts for handling compositional data over time, making it an ideal choice for presenting complex historical data(broad range of years (from 1820 to 2017)) on poverty in a format that is both informative and visually compelling.

Questions 01: Who is Conquering Extreme Poverty in Various Global Regions Across Time? How does the distribution of wealth differ among various income groups?

Plot 02 : Distribution of Wealth Inequality Across Different Income Groups

Dependency Columns:

For Plot 02 dependent columns are "gini", "palma_ratio", "s80_s20_ratio", "p90_p10_ratio", "p90_p50_ratio", "p50_p10_ratio" and "mld"

Distribution of Wealth Inequality Across Different Years

Visualization Descriptions:

Less inequality is often suggested by higher values in the context of metrics such as the Gini coefficient, Palma ratio, or S80/S20 ratio, whereas more inequality is often suggested by lower values.

Darker hues: approaching the color purple, would symbolize a more equitable distribution, where income is dispersed more equally among the populace.

Brighter hues: which resemble yellow more closely, would be indicative of greater inequality and wealth concentration in a smaller number of hands. As an illustration, a country’s level of inequality would be shown by a Gini coefficient that is closer to 0 (darker colors) or closer to 1 (brighter colors). In the same way, lower values for the Palma and S80/S20 ratios would indicate a narrower gap between the wealthiest and poorest groups in society.

Discussion

References

[1] Source Data link : https://ourworldindata.org/grapher/world-population-in-extreme-poverty-absolute?time=earliest..2015

[2] Used Generative AI to know the solutions of the errors link: https://chat.openai.com/

[3] Used some techniques an codes from class lectures ppt file, Link: https://datavizaz.org/

Question 2